System and method for market research within a social network

ABSTRACT

Systems and methods of the present invention provide for one or more server computers communicatively coupled to a network and configured to run, within an active memory of the server computer: a data collection query aggregating user profile data defining a user and product profile data defining products or services; a graph generation module defining a user feature common to a product feature, where a first product sharing a greatest number of features is closest to the user in the graph; a product suggestion module rendering a user interface comprising the first product, a positive response to the first product, and a negative response to the first product. If a positive response is received, the server computer renders the user interface with a second product closest in proximity to the first product, or if a negative response is received, re-generates the graph and renders the user interface comprising a second product in closest proximity to the user, but not sharing features with the first product.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. Provisional Patent Application62/127,686, filed Mar. 3, 2015, and entitled “SYSTEM AND METHOD FORDOMAIN NAME COMMUNITY NETWORK.”

FIELD OF THE INVENTION

The present invention generally relates to the fields of domain namesand market research and specifically to the fields of generating socialnetworks for domain name registrants and entrepreneurs seeking strategicadvice regarding businesses associated with their domain names orproduct ideas.

SUMMARY OF THE INVENTION

The present invention provides systems and methods comprising a servercomputer coupled to a network and configured to run, within an activememory: a data collection module aggregating a plurality of domain namedata; a profile generation module generating a domain name profile fromthe domain name data comprising attributes associated with a firstdomain name; a graph generation module defining domain names sharingattributes with the domain name, a second domain name in the domainnames sharing a greatest number of attributes with the first domain nameand closest, in proximity within a generated graph, to the first domainname; and a domain name strategy suggestion module rendering a userinterface comprising a user interface control that identifies a referralto an administrator for the second domain name and provides, within theuser interface control, a link for contacting the administrator.

The present invention also provides systems and methods comprising aserver computer coupled to a network and configured to run, within anactive memory of the server computer: a data collection queryaggregating user profile data defining a user and product profile datadefining products or services; a graph generation module defining a userfeature common to a product feature, where a first product sharing agreatest number of features is closest to the user in the graph; aproduct suggestion module rendering a user interface comprising thefirst product, a positive response to the first product, and a negativeresponse to the first product. If a positive response is received, theserver computer renders the user interface with a second product closestin proximity to the first product, or if a negative response isreceived, re-generates the graph and renders the user interfacecomprising a second product in closest proximity to the user, but notsharing features with the first product.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a possible system for business strategy and marketresearch within a social network.

FIG. 2 illustrates a more detailed possible system for business strategyand market research within a social network.

FIG. 3 is an example graph used in a possible embodiment for businessstrategy and market research within a social network.

FIG. 4 is an example graph used in a possible embodiment for businessstrategy and market research within a social network.

FIG. 5A is an example user interface used in a possible embodiment forbusiness strategy and market research within a social network.

FIG. 5B is an example user interface used in a possible embodiment forbusiness strategy and market research within a social network.

FIG. 6 is an example user interface used in a possible embodiment forbusiness strategy and market research within a social network.

FIG. 7 is an example user interface used in a possible embodiment forbusiness strategy and market research within a social network.

FIG. 8 is an example user interface used in a possible embodiment forbusiness strategy and market research within a social network.

FIG. 9 is an example user interface used in a possible embodiment forbusiness strategy and market research within a social network.

FIGS. 10A-10C are example user interfaces used in a possible embodimentfor business strategy and market research within a social network.

FIG. 11 is an example user interface used in a possible embodiment forbusiness strategy and market research within a social network.

FIG. 12 is an example user interface used in a possible embodiment forbusiness strategy and market research within a social network.

FIGS. 13A-13C are example user interfaces used in a possible embodimentfor business strategy and market research within a social network.

FIGS. 14A-14B are example user interfaces used in a possible embodimentfor business strategy and market research within a social network.

FIGS. 15A-15C are example user interfaces used in a possible embodimentfor business strategy and market research within a social network.

FIG. 16 is an example user interface used in a possible embodiment forbusiness strategy and market research within a social network.

FIGS. 17A-17D are example user interfaces used in a possible embodimentfor business strategy and market research within a social network.

FIGS. 18A-18B are example user interfaces used in a possible embodimentfor business strategy and market research within a social network.

FIG. 19 is a flow diagram representing method steps within a possibleembodiment for business strategy and market research within a socialnetwork.

FIG. 20 is a flow diagram representing method steps within a possibleembodiment for business strategy and market research within a socialnetwork.

DETAILED DESCRIPTION

Users of a social network may interact with other like-mindedindividuals (e.g., customers, suppliers, peers, consultants, etc.),perhaps to expand business opportunities and/or share strategies andideas. The currently disclosed invention uses a collection of userprofile data (e.g., GoDaddy's 59 million registered domain names) andrelated data to create a social network for individuals and entities,including those looking to start, grow or run an online venture. Thenetwork will be made up of a number of social graphs that identifyrelated individuals, entities, businesses, concepts, etc. and therelationships between them. The disclosed invention also expands theconcept of a social network beyond connections between people to includeideas as the fabric that connects people to other people through thoseideas.

The disclosed invention, therefore, creates a social network betweenlike-minded entities, where individuals, businesses, domain nameregistrants, website operators, market researchers, customers,suppliers, peers, consultants, investors, etc. share business strategiesand ideas in order to expand business opportunities. To facilitate sucha social network, the disclosed system may include a centralizedrepository of information storing a plurality of data associated with anonline entity. In this disclosure, non-limiting examples of onlineentities may include a user of the disclosed system, an online businessrun by the user, a website associated with the online business, a domainname used to access the website, a product or service available throughthe online business and/or website, and/or one or more ideas for a newproduct or service to be offered by the business/website.

A user may input a request for information regarding these entities. Forexample, in some embodiments, the user may be an operator of an onlinebusiness who has just registered one or more domain names for the user'sbusiness. In this example, the domain name(s) may be the user input forthe disclosed system, and the domain names, as user input, may be usedto request contact information for additional users in the socialnetwork that share characteristics with the new domain name registrantand/or the domain name. In other embodiments, the user input for thedisclosed system may be made up of a user profile data about the userand/or an idea for a new product or service created by the user, and theinput data may be used to request and identify related ideas forproducts or services within the social network that sharecharacteristics with the user, the user's product or service idea,and/or products or services that the user has liked within the socialnetwork.

The disclosed system may generate a data profile for each of theidentified entities, where the data profile is made up of a collectionof data aggregated from multiple databases storing customer datarecords, accounting history data records for the customer's business,web server data for a business website, and/or domain name dataassociated with the customer's business website, as non-limitingexamples. Thus, in embodiments where the user input includes one or moredomain names, the domain name's data profile may be generated byaggregating customer data, business accounting history data, websitedata and/or domain name data associated with the input domain name.Similarly, in embodiments where the user input includes user profiledata and/or a product or service associated with the user profile, theuser or product's data profile may be generated by aggregating customerdata, business accounting history data, website data and/or domain namedata associated with the input user profile and/or product/service.

The disclosed system may generate a graph interrelating each of theidentified entities. This graph may demonstrate the relationshipsbetween, and the relevance of, the identified entities, according to theentities' features, also referred to herein as dimensions. For example,in embodiments where domain name data profiles have been generated fromcustomer, business, website and/or domain name data, the disclosedsystem may generate a graph where domain names that share a greaternumber of features are clustered together in closer proximity, ascompared to those domain names sharing a lesser number of thesefeatures. Similarly, in embodiments where user and/or product ideaprofiles have been generated, from customer, business, website and/ordomain name data, for a user and/or product idea, the disclosed systemmay generate a graph where users and/or combinations of product ideasthat share a greater number of features are clustered together in closerproximity than those users and/or product ideas sharing a lesser numberof these features.

Using the generated graph, the disclosed system may generate suggestionsfor strategies to improve the user's business. For example, inembodiments where the generated graph comprises one or more domain namesclustered in close proximity to the domain name(s) input by the user(and therefore sharing the greatest number of common features), thedisclosed system may recommend, to the user that input the domainname(s): websites (e.g., URLs) or contact information (e.g., email ortext number) for successful businesses in a similar industry orgeography to determine important elements of success in their websitedesign or business plan; websites or contact information for businesseshaving unrelated products or services, but that are similar in businessgrowth (e.g., early stage businesses that have recently set up ashopping cart); websites or contact information for professionals tomanage/expand the success of the business (e.g., technology, accounting,marketing or legal professionals); etc.

In embodiments where the generated graph comprises one or more productideas clustered in close proximity to the user's profile, productssubmitted by the user, or products for which the user has input apositive response (and therefore sharing the greatest number of commondimensions), the disclosed system may recommend relevant products to theuser via a user interface, thereby providing a social network thatlearns, from the user actions taken, similar market segments targetedmarketing for specific products and types of products sharing similarfeatures.

A first example embodiment of the disclosed invention may generate asocial network connecting users who are seeking specific businessfeedback around recently registered domain names. To create the socialnetwork, data associated with each domain can be analyzed to learn asmuch as possible about the domain and its related registrant, website,business, venture, concepts, ideas, etc. This could involve analyzingthe domain name itself, keywords in the domain name, traffic to thedomain (including traffic volume, location of origination, and referrerinformation), search engine optimization (SEO) data for the domain,customer account information, website content at the domain, and thelike. The analysis can then identify various data points for each domainand, thereby, concepts, ideas, business type, and/or business associatedwith the domain. Example data points include themes, terms, areas ofinterest, or business category, type, location, size, age, performance,target market, etc. However, the disclosed invention should not belimited to domain names only, but may be augmented to include any dataaggregated by the data aggregation model, as disclosed herein, and thenetworks, graphs, relationships, etc. between this aggregated data.

These data points are then used to create the social network. The socialnetwork can then be used to provide useful leads or referrals to smallbusiness owners using GoDaddy's services or browsing its website.Referrals may be presented as a simple link to the websites of otherrelated businesses or, for those business owners that opt-in, mayinclude contact information for an individual or business. For example,a wedding planner in Phoenix, Ariz. may be referred to nearby flowershops and dress makers, perhaps those whose available data indicatesexperience in wedding floral arrangements and bridal gowns.

Sometimes the referrals may be to other businesses that sell similarproducts or provide similar services or to registrants that maintainwebsites of similar themes. For example, a Website Builder userconstructing a new website for a bike shop could be presented withreferrals to other bike shops around the country, perhaps those whosedata indicates business success. This would allow the user to view thewebsites of the other bike shops and thereby learn what it takes tobuild a successful website. The user could also use the referrals toconnect with other bike shop owners directly to see what they think areimportant elements in a bike shop's website, or perhaps even a businessplan (e.g., what bike brands to carry, etc.).

In other cases, the referrals may be to businesses that sell unrelatedproducts or services but that are similarly situated from a businessgrowth perspective. For example, a new business in the process of addingshopping cart functionality to its website may be presented withreferrals to other business that have only recently set up theirshopping carts. This would allow the user to contact other businessowners that are familiar with the shopping cart setup process. Thus,brand new businesses could be presented with referrals to otherearly-stage businesses to discover what has worked and not worked forthem.

In yet another case, the social network may provide referrals toprofessional service providers (e.g., web designers, lawyers,accountants, tax professionals, marketing firms, etc. also in thenetwork) that could help the business reach the next level of success.For example, if the available data indicates a business is nascent, areferral may be to an in-network (and perhaps local) web design and/ormarketing firm that may be able to improve the business' website toimprove traffic and sales. If the data indicates the business has awell-designed website and growing revenue, referrals may be toin-network (and perhaps local) accounting, tax, and/or legal firms thatmay help the business manage its newfound success.

This social network can also be used to enhance the experience ofwebsite professionals. Because the social network could identify new ornascent businesses, the network could be used to connect website andbusiness developers with those new businesses. In that case, referralscould be made to new business owners identifying developers having aparticular specialty associated with the new business. Alternatively,developers could be provided with referrals to new businesses that arein need of their services.

The social network also may be used to connect like-minded individualswith similar ideas, perhaps enabling them to help each other turn theirideas into reality. In one case, individuals (perhaps local to eachother, or perhaps anywhere around the world) whose domain name-relateddata indicates interest in a common theme (e.g., bikes) may be referredor otherwise prompted to connect, engage, discuss, or otherwise interactaround their common theme. The ability to connect such common-thinkingindividuals, based on the above-described data, is one unique aspect ofthis invention.

Another unique aspect of the disclosed invention, described in moredetail below, includes use of the example data points to identifyfeatures that define users of the invention, including, but not limitedto, a user's industry category, geographic location, and demographics ofadditional users that are associated with the user through a socialnetwork. The data points may also define features of products orservices that the user has shown a particular interest in. These productfeatures may include a title of the product, a description of theproduct, a stage of the entrepreneurial process that the creator of theproduct is in, a language spoken in association with the product, userswithin the social network that are following the progress of theproduct, the demographics of those followers, etc. The features definingthe users and products may be used as factors in determining the typesof products suggested to the user in the future, according to arelevance score calculated for the strength of connections between usersand pairs of products or product ideas that share common features, asdescribed below.

In one embodiment of the present invention suggesting businessstrategies based on relevant domain names, the above-described inventioncould be implemented with data collection, data analysis, and referralor suggested product generation software modules running on one or moreserver computers connected to the Internet.

The present system may be implemented by a computer server configuredwith a number of data processing modules, as described herein. Thecomputer server may comprise any computer or program that providesservices to other computers, programs, or users either in the samecomputer or over a computer network. As non-limiting examples, thecomputer server may comprise application, communication, mail, database,proxy, file, media, web, peer-to-peer, standalone, software, or hardwareservers (i.e., server computers) and may use any server format known inthe art or developed in the future (possibly a shared hosting server, avirtual dedicated hosting server, a dedicated hosting server, a cloudhosting solution, a grid hosting solution, or any combination thereof)and may be used, for example to provide access to the data needed forthe software combination requested by a client. To provide the presentfunctionality, a computer server may implement a number of methods. Suchmethods may be performed by any central processing unit (CPU) in anycomputing system, such as a microprocessor running on at least onecomputer server and, optionally, a client computer system, and executinginstructions stored (perhaps as scripts and/or software, possibly assoftware modules/components) in computer-readable media accessible tothe CPU, such as a hard disk drive on the computer server.

FIG. 1 is a block diagram showing an example computer server configuredin accordance with the present disclosure. Computer server 100 includesa number of data accumulation and processing modules that, whenimplemented together, provide the functionality of the presentdisclosure. As shown in FIG. 1, computer server 100 includes datacollection module 102, profile generation module 104, graph generationmodule 106, and suggestion engine module 108. The modules may be storedin the memory of—and run on—at least one computer server 100. To run themodules on the at least one computer server 100, any of the modules, orany of the combination of the modules, may be accessed within the memoryof the at least one server computer (e.g., the computer server's 100hard drive) and loaded into active memory (e.g., the computer server's100 random access memory), where the instructions for the modules may beexecuted. As non-limiting examples of such software, the presentdisclosure describes in detail the software modules/components that makeup the software combination. These software modules/components maycomprise software and/or scripts containing instructions that, whenexecuted by a microprocessor on a computer server 100 or a clientcomputer in communication with computer server 100, cause themicroprocessor to accomplish the purpose of the module/component asdescribed in detail herein. The software combination may also shareinformation, including data from data sources and/or variables used invarious algorithms executed on the servers and/or clients 100 within thesystem, between each module/component of the software combination asneeded. (note: remember to include something about software being loadedinto active memory of computer server so it matches the claims . . . )

Data collection module 102 is generally configured to collect dataassociated with a number of domain names, a number of users and/or anumber of products or other entrepreneurial ideas, as non-limitingexamples. The data may be collected from a number of disparate datastorage systems, where each data storage system stores information thatis in some way associated with the domain name, the user and/or theproduct or idea for which data is being accumulated. To initiate datacollection, data collection module 102 may be provided with a listing ofdomain names, users and/or ideas. Then, for each domain name, userand/or idea in the listing of domain names, users and/or ideas, datacollection module 102 can access a number of data storage systems tocollect information associated with the domain name, user and/or idea.

For example, a domain name system (DNS) may be accessed to retrieve anumber of DNS records that are associated with the domain name. Acustomer account database, possibly maintained by a domain nameregistrar or registry, could be accessed to retrieve information from acustomer account for the customer that has registered the domain name orthat has submitted a product or other entrepreneurial idea to acommunity of such ideas. In that case, example data retrieved from thecustomer account database may include the name of the customer, the nameand type of any business associated with the domain name, the idea orthe customer, an indication of whether the business offers products orservices, a size of the business, a targeted growth for the business, adate on which the customer account was created, a date on which thedomain name was registered, identities of other domain names that areregistered to the customer, demographic information about the customer,such as the geographic area of their home or an industry category withwhich their business is associated, details for any businesses, relatedbusiness products or product ideas, websites, etc. related to the domainnames, the results of any customer surveys regarding their domain nameor business, a history of recent acquisitions of products or servicesfor or associated with their domain name (e.g., domain name privacyservices, website builder tools, templates or clipart for use with thedomain name, security certificates, SEO services, and the like), searchengine optimization (SEO) history for the domain name or a relatedwebsite, ongoing or historical marketing efforts, geographicalinformation, such as the location of the customer or anticipatedlocation of customers, and the like.

If the customer account is associated with any bookkeeping or businessaccounting software or tools for a business associated with the domainname, data collection module 102 could access those systems to collectdata related to the domain name or its associated business. For example,data collection module 102 could collect data such as a financialhistory of the company (historical sales numbers, trends in changes ofsales), volume of products sold as well as the types of each of theproducts and/or ideas for new products, destinations to which productshave been shipped, gross revenue, and the like.

In some cases, a website that is associated with the domain name couldbe accessed and analyzed by data collection module 102 to gatheradditional information associated with the domain name, thecustomer/user, the associated business, related products or ideas, etc.For example, the keywords on the website and/or associated with a user,business or product could be identified (along with keywords present inthe domain name) and analyzed to determine a type of the website as wellas a type of, or details about, a business, idea, theme, concept, orarea of interest associated with the domain name or website, a targetmarket for the website (this may include determination of both a targetgeographical area for the target market of the website—perhaps basedupon language, and also a target age group for the website), an age ofthe website, a revision history of the website (e.g., how often thewebsite has been changed or updated and by whom), the identification (ifavailable) of any tools used to modify or update the website, and thelike. In some embodiments, the traffic flow to the website can also beanalyzed to identify, for example, the geographical regions from which amajority of the website's traffic originates, the language spoken by themajority of visitors to the website, and the like.

In the case of domain names associated with web developmentprofessionals, various databases may be accessed to identify a list ofpresent and former clients of the web development professionals. Thisinformation can later be used to make recommendations of web developmentprofessionals to domain name registrants that are associated withnascent businesses and may need assistance in developing their webpresence.

FIG. 2 is a block diagram illustrating an example operation of datacollection module 102. As shown in FIG. 2, data collection module 102receives as an input a listing of domain names 200. Having received thelisting of domain names 200, data collection module 102, for each domainname in listing 200, accesses a number of candidate data storage systemsin an attempt to gather information related to the domain name. In somecases, a particular data storage system may contain no informationrelated to a particular domain name. In that case, data collectionmodule 102 would move on to the next data storage system in an attemptto gather at least some information about the domain name. In othercases, a data storage system may contain an incomplete or partial recordof information associated with the domain name. In that case, datacollection module 102 would collect the available information and thenmove on to the next data storage system. As illustrated in FIG. 2, datacollection module 102 is configured in communication with a number ofdata storage systems including DNS 202, customer data records database204, server 206, which hosts the website associated with the domainname, and accounting history database 208. The data storage systemsshown in FIG. 2 are merely exemplary as it should be understood thatdata collection module 102 may be configured in various embodiments tocommunicate with any number of data storage systems to retrieveinformation related to a domain name.

As data collection module 102 accesses the various data storage systemsto collect information and data associated with a domain name, thatinformation and data can be stored in a suitable data repository to beaccessed and retrieved by the other components of computer server 100.

After data collection module 102 has collected the available informationfor each of the domain names contained in the domain name listing,profile generation module 104 is configured to generate a profile foreach of the domain names contained in the domain name listing. Theprofile is configured to describe various attribute of each of thedomain names, which, in many cases, involves describing attributes of abusiness, theme, idea, concept, area of interest, or other entity thatmay be associated, in some way, with the domain names. The attributesmay be referred to herein as dimensions. Depending upon theimplementation of the present system, any number of dimensions may bedefined or calculated for each of the domain names. In some cases, theinformation collected for a particular domain name may be insufficientto calculate a particular dimension for that domain name. In that case,the dimension for that domain name may be null or take on anotherdefault value.

Table 1, below, shows a listing of example dimensions that may becalculated by profile generation module 104 for each domain name in aset of domain names. The left column identifies the dimension, while thesecond column identifies, for each dimension, example data that may havebeen collected by data collection module 102 that may be utilized tocalculate the dimension.

TABLE 1 Dimension Data Source Age of domain name registration DNSrecords Customer account information stored with registrar of the domainname Other domain name registrations Customer account informationBusiness type Customer account information Website keywords Accountingsoftware history Business size Customer account information Accountingsoftware history Business location Customer account information Businesstarget growth % Customer account information Business actual growth %Customer account information Accounting software history Target marketgeographical Customer account information region Website keywordanalysis Actual market geographical Customer account information regionWebsite keyword analysis Accounting software history Domain nameproducts purchased Customer account information Domain name productsrecently Customer account information purchased Age of websiteassociated with Customer account information domain name DNS recordsWebsite keyword analysis Website keywords Website and domain namekeyword analysis Website traffic volume Website hosting analysis Thirdparty traffic volume analysis services Ideas, concepts, themes, orCustomer account information areas of interest Website and domain namekeyword analysis

The values of the various dimensions that may be defined for a domainname may be of varying types. For example, some dimensions may benumerical values, while others may be collections of keywords of textstrings. Still other dimension values may include listings of valuesthat describe particular geographical regions.

After the dimensions have been calculated for the domain names by theprofile generation module 104, graph generation module 106 is configuredto use the dimensions to generate a number of graphs that interrelatethe various domain names on a number of different dimensions. In thepresent disclosure, a graph is a construct that can be used to depict ordefine the relationships between a number of entities. Generally,entities that are interrelated or connected in the graph share somesimilarity that unconnected entities do not (or connected entities aremore strongly related than unconnected entities). In the presentdisclosure, a number of different graphs could be generated for each oneof the various domain names, where each graph focuses upon a differentdimension or combination of dimensions.

FIG. 3 shows an example graph that depicts the relationship between anumber of domain names, where the domain names are grouped based uponlocation and website keywords. Centered in the graph is domain nameazbikes.net 302, a domain name for a business based in Phoenix, Ariz. Inthis example, the domain name is associated with a website upon whichbikes are sold. As can be seen, domain name 302 is directly connected toa number of other domain names that are, themselves, associated withwebsites that contain similar keywords to the website for domain name302 and that are also located in a similar area.

Domain name arizona-extreme-tourism.com 304 is related to domain name302 through an intermediary domain name. This relationship could becreated, for example, because the website associated with domain name304 includes some keywords that relate to biking—perhaps it is one ofthe tourist activities offered on the website. Additionally, because thegeographical region associated with domain name 304 includes Arizona,both domain names 304 and 302 share a similar location.

Domain name gnarly-trails.com 306 is also directly connected to domainname 302. In this example, domain name 306 is associated with a websitethat contains a database of mountain biking trails. The databasecontains trails for locations in both Arizona and Colorado. Becausedomain name 306 is also associated with the location of Colorado, domainname 306 is connected to domain name 308 and, through domain name 308,to domain name 310, where both domain names 308 and 310 are associatedwith biking in Colorado.

In this manner, many different graphs can be generated for the domainnames that have been profiled using any combination of dimensionscalculated by profile generation module 104. For example, graphs couldbe created to interrelate domain names associated with businesseslocated in the same geographical region and having similar target growthpercentages. Another graph may associate businesses that ship the sametypes of products, regardless of the location of the business (suchidentifications could help connect business owners so that they candiscuss best options for shipping, etc.).

Another graph could relate domain names that are associated with nascentbusinesses that are of the same type. A nascent business may be one forwhich a customer has purchased a domain name, but has not associated thedomain name with a website (or only has a temporary, place-holderwebsite) and has not yet formally formed a business. In fact, such agraph need not be limited to business-based relationships. Relationshipsbased on mere ideas in common may suffice. For example, the graph mayinterrelate domain names whose registrants appear to have ideas,concepts, themes, or areas of interest in common, perhaps based ondomain name or website keyword analysis. For example, where such dataindicates a common theme (e.g., bikes) between domain names, the graphmay map relationships between registrants of such domain names.

Still other graphs could be generated to interrelate companies that arelikely in need of professional website and web-business design andengineering assistance. Such a graph may interrelate nascent businesses(e.g., by identifying and interrelating domain names that, even thoughthey are associated with a website, have very little web traffic) basedupon location. Web professionals could then use the graph to identifylocal domain name registrants that may benefit from improving theirassistance in developing and refining an online presence.

Yet another graph may interrelate companies that are consumers ofsimilar online services. Such a graph could be used by an individual whohas just purchased a particular online service (e.g., domain nameprotection, SEO services, hosting services) to identify contacts atother businesses that may be of assistance in setting up those onlineservices. In such a case, it may not be necessary to use business typeas one of the dimensions that is used to interrelate the domain names inthe relevant graph. Because expertise in a particular online servicecould be held by a contact at a completely unrelated business,interrelations between businesses that sell or market very differentproducts or services could be useful as long as the businesses haveimplemented similar online services.

To illustrate, FIG. 4 is graph that interrelates companies that haveinstalled or setup similar online services. As shown, based upon thedomain names themselves, the domain names do not appear to be associatedwith businesses that all sell similar goods or services. Even so, theregistrant of the domain name daves-knick-knacks.net may wish to contactcontacts at either idaho-pet-rescue.com or spapumpsforless.com to getassistance with setting up and configuring particular online servicesbecause, as indicated by the graph of FIG. 4, each of those domain nameshas installed or configured similar online services. Accordingly,contacts at either of those domain names may be able to provide goodtechnical assistance on suggestions of the best way to setup the onlineservices for daves-knick-knacks.net.

Once created, the various graphs could be used by suggestion enginemodule 108 to provide suggested contacts and recommended domain names toa user in a number of different scenarios. In one example, a forum orwebsite could be created that allows a registrant of a domain name toidentify other domain names or contacts with similar ideas, or atrelated businesses that may helpful to the user. For example, thecontacts may help the user brainstorm how to advance their nascent ideaor business, or develop a website for their domain name. FIG. 5A is ascreenshot that illustrates an example user interface for such acommunity website.

As shown in FIG. 5A, the interface includes a number of categories ofrecommendations. The first category, SIMILAR IDEA, provides a listing ofcontacts (perhaps domain name registrants as determined from WHOISrecords that have opted into the network) determined to have ideas,concepts, themes, or areas of interest in common with the user. Byconnecting such like-minded individuals, the embodiments describedherein enable them to share ideas, brainstorm, and perhaps start anonline venture around their common ideas.

Another category, SIMILAR MARKET, provides a listing of domain namesthat are associated with businesses in a similar market to the user. Byusing the listing of the domain names, the user can access the providedwebsites for those domain names to learn what attributes are associatedwith a successful website in their market. In some cases, the user mayeven get ideas for how to improve their own website design havingreviewed the websites of a number of similar businesses.

Another category, SIMILAR ONLINE PRESENCE, provides a listing of domainnames that have a similar online presence to the user. In that case, thedomain names listed have purchased, setup, and/or configured a similarset of online services as the user. In the example depicted in FIG. 5A,registrants of each domain name have elected to opt-in and share theircontact information to the small business forum. Using the contactinformation, therefore, the user may be able to reach out to anindividual with experience in setting up and configuring the same onlineservices. If the list of domain names is sorted so that domain namesassociated with businesses located nearby the user are presentedearlier, the user may be able to selected one of those and setup anin-person meeting, facilitating knowledge transfer.

In a final category, SIMILAR HISTORY, the forum provides a listing ofdomain names that are associated with businesses having a similarhistory to that of the user's business in a category titled SIMILARHISTORY. As such, if the user has a nascent business (e.g., haspurchased a domain name, but is still to setup a website and formallyform the company), the contacts provided may connect the user to othersimilarly-situated businesses. This would allow the user to reach outand make contact with other individuals that are starting businesses andcan share strategies, stories, and techniques.

Similarly, if the user's business is very mature, and is driven by asophisticated website platform, the contacts provided would be to othersimilarly-situated companies. Again, this would allow the user to reachout to other individuals that may be facing the same obstacles anddifficulties and to share techniques and strategies for overcoming thesame.

As shown in FIG. 5A, if the registrant for a domain name has opted intothe small business forum, the registrant's contact information may beprovided, facilitating a connection.

In one embodiment, the community website illustrated in FIG. 5A mayprovide communication and interaction tools known in the art to enableonline engagement, such as instant or direct messaging, video chat,wikis, shared online storage, and the like.

Another embodiment may generate and display a visualization mappingrelated contacts to their geographic location. For example, a user maybe presented with a world map, upon which relevant contacts aregeo-appropriately displayed. Clicking on links may open windows enablingconnection, communication, and engagement as described above. Aselection mechanism may be provided allowing the user to toggle betweencontact overlays (e.g., SIMILAR IDEA, SIMILAR MARKET, SIMILAR ONLINEPRESENCE, SIMILAR HISTORY, etc.).

To illustrate, FIG. 5B depicts an example user interface showing how therelevant contacts may be displayed over a geographical region. Withreference to FIG. 5B, the user can select, via a number of checkboxes502, one or more categories of contacts that are to be displayed withinthe user interface. After the one or more categories have been selected,an appropriate geographical region is determined that encompasses thelocations of all of the suggested contacts for the user in the selectedcategories. This may be necessary because different categories may tendto include contacts that are spread throughout different geographicalregions. For example, contacts contained within the SIMILAR MARKETcategory may be generally restricted to the geographic area of themarket. In contrast, the SIMILAR IDEAS contacts may not be restricted toa particular geographical region and may be distributed throughout theglobe.

In the example depicted in FIG. 5B, the user has selected the “SIMILARMARKET” category, and so the depicted contacts are those belonging tothe user's market, which generally includes North America. If the userwere to select a different set of categories for which contacts are tobe displayed (e.g., by selecting or unselecting one of checkboxes 502),the appropriate geographical region would be re-calculated for thecontacts contained within the selected categories and the newgeographical region would be displayed in the user interface.

As shown, a number of potential contacts are depicted within the userinterface at their respective locations. In this example, the user hasselected the contact ride-ny.net, for example, by clicking or tappingupon the contact. In response a contact box 504 is displayed thatprovides the user with a number of mechanisms to get into contact withthe registrant or owner associated with the selected domain name.

In other embodiments, the graphs can be utilized to provide suggesteddomain names and contacts as the user browses through and interacts witha domain name management website. As the user navigates through thevarious web pages of the website, different sets of suggested domainnames or contacts could be provided that are of particular relevance tothe web page currently being viewed by the user.

For example, FIG. 6 depicts a user interface that may be displayed whilethe user interacts with the domain name management website to addshopping cart functionality to their website. Within the user interface,the user is provided with a number of domain names and related contactinformation, where the domain name registrants of the listed domainnames have themselves recently added shopping cart functionality totheir own websites. By reaching out to one of the provided contacts,therefore, the user may be able to speak with an individual that hasfamiliarity with the shopping cart functionality and that may suggestoptimum ways of configuring the software for the user's business.

Although the primary dimension by which the domain names suggested inFIG. 6 are sorted is domain name recently purchased (see Table 1, above)in order to identify domain names that have recently purchased shoppingcart functionality, a secondary dimension by which the domain names maybe sorted is business type. In that case, the suggested domain names mayinclude those for which shopping cart functionality has recently beenpurchased or added, and are associated with a similar business.

A similar set of suggested domain names and related contacts could beprovided on any web page of the domain name management website. FIG. 7shows another example user interface where domain names and contactinformation can be suggested as part of the SEO configuration process.

As discussed above, the various graphs may be utilized to assist webprofessionals (e.g., website designers and engineers, businessconsultants, social media managers, and the like) to identify potentialnew clients and, similarly, nascent business owners (or other businessowners) to identify web professionals with which to collaborate.

FIG. 8, for example, shows a user interface that a web professional mayutilize to identify potential new clients. As illustrated, one or moregraphs that define interrelationships between domain names based onlocation and status of a business associated with a domain name havebeen analyzed to identify nascent businesses in the vicinity of a webprofessional. If the registrants for those domain names have opted in tothe program, their contact information may be provided so that the webprofessional can reach out to the registrant to offer their services andassistance.

Conversely, FIG. 9 shows a user interface that may be used to assist anascent business owner to identify a suitable web professional forassistance. In the user interface, the user is provided with a listingof domain names and contact information for web professionals that haveexperience working with other companies of the same business type andare local to the user.

In each of the examples shown in FIGS. 5-9, the listing of domain names(and, potentially, contact information) can be identified by analyzingone or more of the graphs generated by graph generation module 106. Thesuggested domain names may, for example, include those that are closestto the user's domain name in a particular graph. In some cases, the setof identified domain names can be sorted with various preferences. Forexample, the domain names may be sorted so that domain names associatedwith businesses that are local or nearby the user are presented first,with domain names associated with more distant businesses beingpresented later. In general, once a number of domain names areidentified, they can be sorted using any further combination ofdimensions, as described above. Thus, the disclosed invention mayinclude a social network connecting users who are seeking specificbusiness strategy feedback around recently registered domain names.

The disclosed invention may also generate a social network connectingusers who are seeking specific business feedback around one or moreproduct or service ideas. In these embodiments, the user input 200 forthe disclosed system may be made up of a user profile data about theuser and/or an entrepreneurial idea for a new product or service createdby the user. The input data 200 may be used to request and identifyrelated ideas for products or services stored within the social networkthat share characteristics with the user, the user's product or serviceidea, and/or products or services that the user has liked within thesocial network. The user or product's data profile may be generated byaggregating customer data 204, business accounting history data 208,website data 206 and/or domain name data 202 associated with the inputuser profile and/or product/service. Using this user or product dataprofile, the disclosed system may generate a graph where users and/orcombinations of product ideas sharing a greater number of features areclustered together in closer proximity than those users and/or productideas sharing a lesser number of these features. The disclosed systemmay then recommend relevant products to the user via a user interface,thereby providing a social network that learns, from the user actionstaken, similar market segments and targeted marketing for specificproducts and types of products sharing similar features.

Returning to FIG. 2, the user input 200 received for data collectionmodule 102 should not be limited to a list of domain names, aspreviously described, but may also include input related to any of theentities described herein whose features are defined according to datawithin the DNS 202, customer records database 204, web server 206,accounting history database 208, and/or any other data sources describedherein. As non-limiting examples, the input 200 for data collectionmodule 102 may receive any data related to users of the system,businesses operated by the users of the system, websites related tothese businesses, products or services available through thesebusinesses and/or websites, etc. Thus, FIG. 2 may also includevariations of the data to be input and stored according to the exampleblock diagram illustrating an example operation of data collectionmodule 102.

Specifically, data collection module 102 may receive as an input anycombination of data regarding entities such as users, businesses,websites, products, services, etc. Having received the input associatedwith these entities, data collection module 102, for each received inputdata, may access the candidate data storage systems in an attempt togather related information and store that information in a suitable datarepository in association with the appropriate entity profile, analogousto the steps described above, to be accessed and retrieved by the othercomponents of the computer server 100.

After data collection module 102 has collected the availableinformation, profile generation module 104 may be configured to generatea profile for each of, or any combination of, the entities for which thedata was input. The profile may be configured to describe variousattributes or features of each, which, in many cases, involvesdescribing attributes or features of a user, business, product, theme,idea, concept, area of interest, or other entity that may be associated,in some way, with the input data for the entities. As above, theseattributes or features may be referred to herein as dimensions.Depending upon the implementation of the present system, any number offeatures and/or dimensions may be defined or calculated for each of theinput entities, analogous to Table 1 above.

Computer server 100 may receive and analyze these dimensions as featuresassociated with users, businesses, websites, products, services, etc.These features then become factors in determining the strength ofrelationships between these entities, according to a number of commonfeatures that the entities share. As above, the values of the variousfeatures may be of varying types. Some features may be numerical values,while others may be collections of keywords of text strings. Still otherfeature values may include listings of values that describe particulargeographical regions or an industry category associated with a user,business, website, product, service, idea, etc.

For users, non-limiting examples of features may include a customerprofile for each user, which may further include demographics for theuser, actions taken by the user (e.g., liking, following, and/orcommenting on products with features of interest to the user, discussedbelow), etc. These features and dimensions may be generated and storedin association with the user profile according to data received from thedata sources, as keywords within strings from a website about thebusiness or product, for example. These keywords may then be used asfactors in matching to other users and/or products.

For businesses and/or websites, non-limiting examples of features mayinclude an industry category for the business or website (e.g.,restaurant business, web development business, etc.), a business' statuswithin the entrepreneurial process (e.g., new business, establishedbusiness, multi-billion dollar business), etc. In some embodiments, thisindustry category may be identified through keywords from the domainname, business name, website, product names or descriptions, etc., or asan explicit category defined with in the user profile, or as otherwiseidentified within the data sources.

For geography, non-limiting examples of features may include thegeography of the user and/or business. In some embodiments, the userand/or business' geography may be identified according to: a geographydefined in the user profile; an internet protocol (IP) address of aclient computer operated by the user or the host of the website;business records indicating website traffic and/or product sales in aparticular geographic area; languages spoken in relation to e-commerceactivity for a product or service, and by extension, the primarygeographical area associated with that language; etc.

After the profile generation module 104 calculates and identifies thefeatures of the users, businesses, websites, products, services, etc.,graph generation module 106 may use the dimensions to generate one ormore graphs, as explained above, that interrelate the various entitieson a number of different dimensions. In the present disclosure, a numberof different graphs could be generated for each one of the variousentities, where each graph focuses on a different dimension orcombination of dimensions interrelating entities with other entities(e.g., showing relationships between a user and a product), or with likeentities (e.g., showing relationships between a first product idea and asecond product idea).

Users may display these details and relationships for any of thedisclosed entities using any combination of software described herein.In one embodiment, users may download and install, on a client device, asoftware to graph connections between the features identified withinuser profiles and the features identified within product profiles, andmay further recommend additional relevant products to users. Users mayidentify, using a user interface within the software, products thatinclude the user's preferred features. The software may identify and usethese features as factors to determining relevant products that sharethese features (and therefore have a stronger relevance connection), todisplay to the user for user feedback.

Once the software is installed, the client computer may receive input toaccess user profile data for the user. In some embodiments, theinstalled software may require authentication for the user, such as ausername or password, to access a user profile account. In otherembodiments, the user may use the software during a trial period (e.g.,24 hours) to determine whether a product presented by the user isreceiving positive feedback from other users, in which case the userwill need to create a user profile account. In some embodiments, theuser may import data from a social networking site, possibly byaccessing an API or another data stream for the social networkingwebsite. The user and/or computer server 100 may download the userinformation, possibly into a user profile in the customer recordsdatabase 204, thereby providing the data repository with features thatdefine the user. In these embodiments, the user may log into the user'sprofile account and/or the social media website account to authenticatethemselves.

The user may then review a tutorial tour, be prompted to create aproduct idea, and begin the product idea input process as seen in FIGS.10A-10C. This process may provide means for a user to post a new productidea, receive feedback from a social network community, and identifyfeatures and/or characteristics of users interested in the product idea,in order to improve target marketing for the product idea.

The installed software may include a user interface, such as that seenin FIG. 11, to define the features of the product idea. In this exampleembodiment, the features may include a title or headline for the productidea (e.g., “Cat grass weekly subscription”), a description of theproduct idea, possibly explaining why the product idea is unique (e.g.,“Get a weekly delivery . . . ”), and an image of the product idea,chosen by the user. As non-limiting examples, the picture may beuploaded from a user library, a camera or stock photos, such as Flickr.Additional features received from the user (not shown) may include acompany name, a geographic location for the company, a name of anentrepreneur/user that posted the product idea, etc. The user may thenpost the product idea as seen in FIG. 12, and the product idea featuresdata may be stored within the data repository in association with theuser, possibly within a product idea profile created by the profilegeneration module 104.

As seen in FIG. 12, the disclosed invention may include variousembodiments with specific variations on the described product idea. Asnon-limiting examples, the product idea may be stored for a limited time(e.g. 24 hours), in which a certain number of additional users (e.g.,10), who may be following the progress of the product idea, may providea positive response to the product idea (described as liking, loving orfollowing herein). In this example embodiment, if the minimum requiredthreshold of followers is not reached, the product idea may be archived,where nothing but the title is available to any other users except thecreating user, who may then re-submit the idea later, if they choose.However, if the minimum required threshold is reached, the followers maybecome mentors, investors or customers for the user and/or the user'sproduct. Each user of the system may access their individual accountsand create and post product ideas.

The installed software may also include a home page for each user inorder to provide feedback for product ideas posted by other users. Insome embodiments, after reviewing a tutorial tour such as that seen inFIGS. 13A-13C instructing users how to give feedback on other productideas, each user may access their home page, such as that seen in FIGS.14A-14B, which may display product ideas from other users which arerelevant to the features within the user profile and/or the features ofproduct profiles of ideas posted by the user.

To determine the relevance of each of the product ideas in the datarepository that may be displayed to the user, computer server 100 and/orsuggestion engine module 108 may analyze the user profile for the usergenerated by profile generation module 104, using the data collected bydata collection module 102 and defining the features of the user, and/orfeatures associated with the user's business or website, such as theuser's geographic location, industry category, and/or product keywordsassociated with any products, website content, domain name, etc. relatedto the user or the user's business.

Suggestion engine module 108 may then define the user or user'sbusiness, products, website, domain, etc. according to the features ofthese entities, and use these features as factors to identify commonfeatures between the current user (and/or product ideas submitted by thecurrent user), and product ideas submitted by other users. Suggestionengine module 108 may analyze a product idea profile for each of theproduct ideas generated by profile generation module 104, using the datacollected by data collection module 102 and defining the features ofeach product idea. These features may include the product'stitle/headline or description, the geographic region associated withsales of the product idea, the geographic region of the user thatsubmitted the product idea, the geographic region of followers who haveprovided positive feedback for the product idea, an industry categoryfor the product idea, product keywords associated with the product idea,a website content describing the product idea, the domain name for thewebsite, etc.

For each product profile that shares a common factor/feature with thecurrent user's profile (possibly including product idea profilessubmitted by the user), the computer server 100, suggestion enginemodule 108 and/or graph generation module 106 may calculate an ideascore that is unique and mutually exclusive between each product ideaand the current user and/or the user's ideas. The idea score may reflectthe number of common features shared between the user profile and eachof the product idea profiles, where a higher score reflects a greaternumber of common features, and therefore a stronger connection betweenthe user and the product idea, and a lower score indicates a lowernumber of common features and therefore a weaker connection between theuser and the product idea. As non-limiting examples, a higher idea scoremay reflect a high instance of common keywords, or a common geography orindustry category, between the user profile and the product ideaprofile. Graph generation module 106 may then generate a graph from theidea scores, where the ideas with the strongest connection are closestin proximity, within the graph, to the user.

Computer server 100 and/or suggestion engine module 108 may then rendera user interface to be displayed on the home page of the installedprogram, with the user interface displaying one or more product ideasdetermined to be in closest proximity to the user within the graphand/or having the highest idea scores. In some embodiments, a pluralityof product ideas may be displayed on the home page in descending orderof proximity or idea score. The user interface may then be transmittedto a client device for display, as seen in FIGS. 14A-14B.

As seen in FIG. 14A-14B, the rendered and displayed home page mayinclude one or more user interface controls allowing a user to like orskip (which may indicate neutral or negative feedback in variousembodiments) each of the displayed product ideas. The user interfacecontrols may allow a form of quick feedback allowing the user to inputtheir level of interest in each product idea. As seen in FIGS. 14A-14B,the user interface control may include sliding the idea one direction tolike the idea and the opposite direction to skip. This should in no waylimit the scope of the invention. Any user interface control known inthe art allowing a user to indicate positive or negative feedback may beused.

For each user feedback received, the computer server 100, suggestionengine module 108 and/or profile generation module 104 may determinewhether the response feedback for each of the suggested product ideaswas positive or negative. The computer server 100 may then analyze thefeatures of each of the suggested product ideas for which the userfeedback was received. For each of the product ideas receiving apositive response, the computer server 100 may assign a weight to eachof the features of the product idea receiving the positive response,thereby creating a higher idea score for each of the product ideashaving these features in common, and moving each of these featurescloser in proximity to each other and to the profile for the currentuser. Similarly, for each of the product ideas receiving a negativeresponse, the computer server 100 may assign a weight to each of thefeatures of the product idea receiving the negative response, therebycreating a lower idea score for each of the product ideas having thesefeatures in common and moving each of these features further inproximity to the profile for the current user (though closer to eachother, since they share common features).

Each pair of product ideas may therefore also have an idea score that isunique and mutually exclusive between the pair of ideas. As with productideas and users, the idea score between product ideas may be determinedby the number of common features between the two product ideas, wherethe higher the number of common features, the higher the idea score andthe closer in proximity the two ideas are within the generated graph.

Thus, in some embodiments, upon receiving feedback from a user based onthe user's action (e.g., selecting one of the displayed productsrelevant to the user's idea or selected idea), a new idea may bedisplayed. To ensure relevancy to the originally displayed ideas of anynew ideas displayed, and to ensure high engagement, at least one of theoriginally displayed and/or selected suggested products/services shouldhave a very high relevance score, which is a function of the user'spreviously selected and/or followed ideas (i.e., the idea scores betweenthese and the new idea should share a high number of common features).

Specifically, a relevance score for a new idea may be a function of theidea score for the new idea, as compared to the average idea score forthe ideas previously followed by the user, which may be expressed asfollows:

RelevanceScore(New)=F(IdeaScore(New,Followed))

In other words, the relevance score of the new idea should be a highidea score relative to the average idea score of the previously followedideas, which may be calculated by summing the total idea scores for allideas followed by the user, and dividing the sum by the total number ofideas followed by the user. Thus, if the user is currently followingthree ideas, whose idea scores are 7, 8 and 9 respectively, the averageidea score for the ideas currently being followed by the user is 8. Thenew ideas suggested to the user should therefore also have an ideaand/or relevance score of 8 or above.

Therefore, in response to the user's feedback, graph generation module106 may then re-generate the graph, according to the weights assignedresponsive to the user feedback. Those product ideas sharing a higherweighted features may be given a higher idea score and moved closer inproximity to the user profile and to each other. Those product ideasincluding the lower weighted features may be moved further in proximityto both the product ideas having received a positive response from theuser, as well as the user profile, as the user has indicated apreference for product ideas that do not include these features.

Computer server 100 and/or suggestion engine module 108, may analyze there-generated graph to determine one or more product ideas in closestproximity to the product ideas having received positive feedback, andthat have not previously been presented to the user for feedback. Thesuggestion engine module 108 may then render the user interface,including at least one product idea in closest proximity to the productideas having received positive feedback, and that have not previouslybeen presented to the user for feedback. Computer server 100 may thentransmit the user interface to the client device for display, and theprocess may repeat, refining the graph and suggested product ideas eachtime user feedback is received.

In some embodiments, the generated graph may comprise a user interfaceelement representing the graph (e.g., a user graphic element displayedon a web page) allowing a user to see relationships between entities,and may further provide the user with specific strategic suggestions.This idea graph may comprise an idea graph (similar to the social graphshown in FIGS. 3-4), the idea graph being displayed on a user interfacethat displays the proximity of ideas and/or follower demographics withina graph according to at least one common specific factor and/or feature(e.g., idea concepts clustered within a geography).

Computer server 100 may render the graph for display, and may furtheridentify and render one or more business strategy insights according tothe proximity of ideas within the idea graph (which may be displayedvisually). As non-limiting examples, these business strategy insightsmay include: determining, based on trend data, whether a business ideawill likely succeed; determining whether a business idea will likelyhave high interest in a geography with little competition; identifyfollowers of successful business ideas relevant to the user's idea thatwould be good advisors and mentors; offering visibility into differenttrends as a subscription service or app development, possibly in-house;idea/business generation based on ideas popular in a geographic area,and user lives in similar geography and profile suggests similarinterests.

Returning now to FIGS. 14A-14B, for each product idea displayed on theuser's home page, the user may select an option, such as clicking on theidea, as a non-limiting example, to display and view details about theselected product idea. In some embodiments, the user may select todisplay/view the details of the product idea by clicking on the icon forthe product idea, or selecting a “view details” link or other userinterface control. In response to the user's selection, computer server100 and/or profile generation module 104 may render a product ideadetails page, displaying the title/headline, description and/or imagefor the product idea as stored in the product idea profile. Computerserver 100 may then transmit the product idea details page to the clientdevice for display, similar to that seen in FIGS. 13B-13C.

The user interface may also include an options for the user to followthe product idea, as seen in FIG. 13B. By following or “loving” aproduct idea, the user may follow the progress of the idea and beinvolved with its development. As described below, this encouragementmay be in the form of answering questions created by the user thatposted the product idea, and commenting on the response to thequestions. In some embodiments, the encouragement may be in the form ofdirect messaging the user that posted product idea, and may be availablefrom the product idea details page.

As each product idea receives new followers, computer server 100 mayaccess the user profile generated by the profile generation module 104for each of the product idea's followers, and may identify demographicdata within the user profile for each of the followers, possiblycollected and stored in the data repository by data collection module102. Graph generation module 106 may analyze the demographic data foreach of the product idea's followers to identify common demographics.Using these common demographics, graph generation module 106 maygenerate a graph representing the most common user demographics that aremost relevant to the product idea. This graph may be used to determineproduct ideas receiving positive feedback from users sharing thesecommon demographics.

As a non-limiting example, a first and a second product idea mayoriginate from a first bakery in San Francisco, Calif., and a secondbakery in San Francisco, Calif. respectively. Each of these productideas clearly share an industry category feature and a geographicfeature, and thus may be assigned a mutual idea score of 7 in thisexample. However, after analysis of the demographics within the userprofile for each of the product ideas' followers, computer server 100may determine that the average age of followers for the first bakery is20, while the average age of the followers for the second bakery is 50.

A third product idea may originate from a sake bar in Oakland, Calif.,where, after analysis of the demographics for the followers of the sakebar, computer server 100 determines that the average age of thefollowers is 20. This third product idea may generally share a relevantindustry category feature and geography feature, in that the sake bar isgenerally in the food services industry and is in the same state as thebakeries. Graph generation module 106 may therefore generate a graph inwhich all three product ideas are included, but in the initialgeneration of the graph, the first two ideas from the bakeries may becloser in proximity than either is to the sake bar because of theirshared industry category and geographic features.

However, in some embodiments, the age demographic feature may have ahigher weight in determining the idea score between the sake bar productidea and the first bakery idea, for example. By considering thefollowers' profile data when calculating the idea score, the accuracy ofthe relevance between product ideas may be increased in theseembodiments. Thus, because the sake bar and the first bakery both havefollowers whose average age, according to the user profile demographic,is 20, the mutual idea score between the sake bar and the first bakerymay be 8 in this example. This means that the mutual idea score is nowhigher than that for the two bakeries, and the sake bar and first bakerywould be closer in proximity within the generated graph.

As noted above, in some embodiments, the user may create an idea, andwait a fixed period (e.g., 24 hours) to determine if the number offollowers has reached a threshold amount (e.g., 10) to continue theproduct review process. If, at the end of the fixed period the number offollowers is above the threshold amount, the user may be prompted with atutorial tour such as that seen in FIGS. 15A-15C, instructing the userto provide yes/no questions, which followers can answer, and for which areport may be generated, displaying the compiled answers, and providingthe user insights into guiding the product idea. In some embodiments,the number of questions that can be asked by a user for a product islimited to a specific number (e.g., 5 questions), and a fixed period(e.g., 24 hours) may be required between questions. However, the usermay earn additional questions by giving feedback on product ideas byother users and providing responses to their questions. Followers may begiven 7 days to answer questions, as a non-limiting example.

As seen in FIG. 16, a user interface may be provided for users to askfollow up questions to collect user insights and guide the product idea.As product questions are provided, and as users like specific productideas, they may be prompted to provide additional direction and insightsinto the product. Computer server 100 may therefore provide a tutorialtour such as that seen in FIGS. 17A-17D, instructing the user on how toanswer the questions provided for the product idea. For each productidea the user follows, computer server 100 may render, transmit anddisplay a user interface similar to that seen in FIGS. 18A-18B, whereinthe user may answer the yes/no question, provide additional feedback,and/or review the results of all followers for the question.

FIGS. 19-20 are flow diagrams demonstrating the two embodiments of thedisclosed invention for generating a social network for suggestedbusiness strategies and market research within a social network. In FIG.19, at least one processor executes instructions causing a servercomputer, coupled to an electronic network, to run, within an activememory of the server computer: a data collection module executing atleast one data query aggregating, from a plurality of data sources, aplurality of domain name data received through the electronic network(Step 1900); a profile generation module generating, from the domainname data, a domain name profile comprising a plurality of attributesassociated with a first domain name (Step 1910); a graph generationmodule defining a plurality of domain names sharing at least one of theplurality of attributes with the domain name, wherein a second domainname, in the plurality of domain names, sharing a greatest number of theplurality of attributes with the first domain name, is closest, inproximity within a generated graph, to the first domain name (Step1920); a domain name strategy suggestion module rendering a userinterface comprising a user interface control that both identifies areferral to an administrator for the second domain name; and provides,within the user interface control, a link for contacting theadministrator (Step 1930).

In FIG. 20, at least one processor executes instructions causing aserver computer, coupled to an electronic network, to run, within anactive memory of the server computer: a data collection module executingat least one data query aggregating, from a plurality of data sourcesand through the electronic network, a plurality of user profile datadefining a user of a client computer coupled to the electronic networkand a plurality of product profile data defining a plurality of productsor services (Step 2000); a graph generation module defining at least oneuser feature in the plurality of user profile data common to at leastone feature in the plurality of product profile data, wherein a firstproduct in the plurality of products or services, and sharing a greatestnumber of features with the user profile data, is closest, in proximity,within a generated graph, to the user (Step 2010); a product suggestionmodule rendering a user interface comprising the first product, a firstuser interface control encoding a positive response to the firstproduct, and a second user interface control encoding a negativeresponse to the first product (Step 2020). The server computer is thenconfigured to: transmit, via the electronic network, the user interfaceto the client computer; decode a transmission received via theelectronic network and encoding the positive response or the negativeresponse; and responsive to the transmission encoding the positiveresponse (Step 2030), render the user interface comprising a secondproduct sharing a greatest number of features and closest in proximitywith the first product within the generated graph (Step 2040);responsive to the transmission encoding the negative response (Step2050): re-generate the graph, wherein the second product sharing thegreatest number of features with the user, but not with the firstproduct, is closest in proximity, within the generated graph, to theuser (Step 2060). The server computer may then render the user interfacecomprising the second product.

The invention is described in embodiments in the present descriptionwith reference to the Figures, in which like numbers represent the sameor similar elements. Reference throughout this specification to “oneembodiment,” “an embodiment,” “one implementation,” “an implementation,”or similar language means that a particular feature, structure, orcharacteristic described in connection with the embodiment is includedin at least one embodiment of the present invention. Thus, appearancesof the phrases “in one implementation,” “in an implementation,” andsimilar language throughout this specification may, but do notnecessarily, all refer to the same embodiment.

The described features, structures, or characteristics of the inventionmay be combined in any suitable manner in one or more implementations.In the above description, numerous specific details are recited toprovide a thorough understanding of implementations of the invention.One skilled in the relevant art will recognize, however, that theinvention may be practiced without one or more of the specific details,or with other methods, components, materials, and so forth. In otherinstances, well-known structures, materials, or operations are not shownor described in detail to avoid obscuring aspects of the invention.

Any schematic flow chart diagrams included are generally set forth aslogical flow-chart diagrams. As such, the depicted order and labeledsteps are indicative of one embodiment of the presented method. Othersteps and methods may be conceived that are equivalent in function,logic, or effect to one or more steps, or portions thereof, of theillustrated method. Additionally, the format and symbols employed areprovided to explain the logical steps of the method and are understoodnot to limit the scope of the method. Although various arrow types andline types may be employed in the flow-chart diagrams, they areunderstood not to limit the scope of the corresponding method. Indeed,some arrows or other connectors may be used to indicate only the logicalflow of the method. For instance, an arrow may indicate a waiting ormonitoring period of unspecified duration between enumerated steps ofthe depicted method. Additionally, the order in which a particularmethod occurs may or may not strictly adhere to the order of thecorresponding steps shown.

Although the present invention has been described with respect topreferred embodiment(s), any person skilled in the art will recognizethat changes may be made in form and detail, and equivalents may besubstituted for elements of the invention without departing from thespirit and scope of the invention. Therefore, it is intended that theinvention not be limited to the particular embodiments disclosed forcarrying out this invention, but will include all embodiments fallingwithin the scope of the appended claims.

The invention claimed is:
 1. A system comprising at least one processorexecuting instructions causing a server computer, coupled to anelectronic network, to: run, within an active memory of the servercomputer, a data collection module executing at least one data queryaggregating, from a plurality of user, business, website or domain namedata sources, and through the electronic network: a plurality ofbusiness feature data defining a business managed by a user of a mobiledevice coupled to the electronic network; and a plurality of productfeature data defining a plurality of products or services provided bythe business; run, within the active memory of the server computer, arelevancy graph generation module defining at least one business featurein the plurality of business feature data common to at least one featurein the plurality of product feature data, wherein a first product in theplurality of products and services, and sharing a greatest number offeatures with the business, is closest, in proximity, within a generatedrelevancy graph, to the business; run, within the active memory of theserver computer, a product suggestion module rendering a product feeduser interface comprising: the first product; a directional image sliderencoding a positive response to the first product via sliding an imageof the product in a first direction; and the directional image sliderencoding a negative response to the first product via sliding the imagein a second direction; transmit, via the electronic network, the productfeed user interface to the mobile device; decode a transmission receivedvia the electronic network and encoding the positive response or thenegative response; responsive to the transmission encoding the positiveresponse, render the product feed user interface comprising a secondproduct sharing a greatest number of features and closest in proximitywith the first product within the generated relevancy graph; responsiveto the transmission encoding the negative response: re-generate thegenerated relevancy graph, wherein the second product, sharing thegreatest number of features with the business, but not with the firstproduct, is closest in proximity, within the generated relevancy graph,to the business; render the product feed user interface comprising thesecond product.
 2. The system of claim 1, wherein the second product isidentified as having an idea score greater than or equal to a relevancyscore calculated according to an average score of a plurality ofproducts receiving a positive response from the user.
 3. The system ofclaim 1, wherein the plurality of business feature data and theplurality of product feature data comprise a theme, idea, concept, areaof interest comprising: at least one numeric value; or a plurality ofkeywords or text strings.
 4. The system of claim 1 wherein the at leastone business feature in the plurality of business feature data, and theat least one feature in the plurality of product feature data comprise:at least one keyword defining a title or a description of the at leastone business feature or the at least one feature; a geography associatedwith the at least one business feature or the at least one feature; anindustry category associated with the at least one business feature orthe at least one feature; or at least one additional user associatedwith the at least one business feature or the at least one feature, theuser having input the positive response to the first product or thesecond product.
 5. The system of claim 4, wherein the at least onefeature in the plurality of product feature data determines acalculation of an idea score defining a strength of common featuresbetween the business, the first product or the second product.
 6. Thesystem of claim 5, wherein at least one additional business featureassociated with at least one additional business comprises at least onedemographic feature given a preferential weight in the calculation ofthe idea score.
 7. The system of claim 1, wherein the web page furthercomprises: a graphic comprising a visualization of the generatedrelevancy graph; and at least one business strategy comprising: alikelihood of success of the first product or the second product; alikelihood of interest for the first product or the second product in aspecific geographic area; at least one competitor with similar productsin the specific geographical area for the first product or the secondproduct; or at least one successful business relevant to the firstproduct or the second product.
 8. A system comprising at least oneprocessor executing instructions causing a server computer, coupled toan electronic network, to: run, within an active memory of the servercomputer, a data collection module executing at least one data queryaggregating, from a plurality of data sources and through the electronicnetwork: a plurality of user profile data defining a user of a clientcomputer coupled to the electronic network; and a plurality of productprofile data defining a plurality of products or services; run, withinthe active memory of the server computer, a graph generation moduledefining at least one user feature in the plurality of user profile datacommon to at least one product feature in the plurality of productprofile data, wherein a first product in the plurality of products orservices, and sharing a greatest number of features with the userprofile data, is closest, in proximity, within a generated graph, to theuser; run, within the active memory of the server computer, a productsuggestion module rendering a user interface comprising: the firstproduct; a first user interface control encoding a positive response tothe first product; and a second user interface control encoding anegative response to the first product; transmit, via the electronicnetwork, the user interface to the client computer; decode atransmission received via the electronic network and encoding thepositive response or the negative response; responsive to thetransmission encoding the positive response, render the user interfacecomprising a second product sharing a greatest number of features andclosest in proximity with the first product within the generated graph;responsive to the transmission encoding the negative response:re-generate the graph, wherein the second product sharing the greatestnumber of features with the user, but not with the first product, isclosest in proximity, within the generated graph, to the user; renderthe user interface comprising the second product.
 9. The system of claim8, wherein the second product is identified as having an idea scoregreater than or equal to a relevancy score calculated according to anaverage score of a plurality of products receiving a positive responsefrom the user.
 10. The system of claim 8, wherein the plurality of userprofile data and the plurality of product profile data comprise a theme,idea, concept, area of interest comprising: at least one numeric value;or a plurality of keywords or text strings.
 11. The system of claim 8wherein the at least one feature in the plurality of user profile data,and the at least one feature in the plurality of product profile datacomprise: at least one keyword defining a title or a description of theat least one feature; a geography associated with the at least onefeature; an industry category associated with the at least one feature;or at least one additional user associated with the at least one featureand having input the positive response to the first product or thesecond product.
 12. The system of claim 11, wherein the at least onefeature in the plurality of product profile data determines acalculation of an idea score defining a strength of common featuresbetween the user, the first product or the second product.
 13. Thesystem of claim 12, wherein the at least one feature associated with theat least one additional user comprises at least one demographic featuregiven a preferential weight in the calculation of the idea score. 14.The system of claim 8, wherein the user interface further comprises: agraphic comprising a visualization of the generated graph; and at leastone business strategy comprising: a likelihood of success of the firstproduct or the second product; a likelihood of interest for the firstproduct or the second product in a specific geographic area; at leastone competitor with similar products in the specific geographical areafor the first product or the second product; or at least one successfulbusiness relevant to the first product or the second product.
 15. Amethod comprising the steps of: running, within an active memory of aserver computer coupled to an electronic network, a data collectionmodule executing at least one data query aggregating, from a pluralityof data sources and through the electronic network: a plurality of userprofile data defining a user of a client computer coupled to theelectronic network; and a plurality of product profile data defining aplurality of products or services; running, within the active memory ofthe server computer, a graph generation module defining at least oneuser feature in the plurality of user profile data common to at leastone product feature in the plurality of product profile data, wherein afirst product in the plurality of products or services, and sharing agreatest number of features with the user profile data, is closest, inproximity, within a generated graph, to the user; running, within theactive memory of the server computer, a product suggestion modulerendering a user interface comprising: the first product; a first userinterface control encoding a positive response to the first product; anda second user interface control encoding a negative response to thefirst product; transmitting, by the server computer, via the electronicnetwork, the user interface to the client computer; decoding, by theserver computer, a transmission received via the electronic network andencoding the positive response or the negative response; responsive tothe transmission encoding the positive response, rendering, by theserver computer, the user interface comprising a second product sharinga greatest number of features and closest in proximity with the firstproduct within the generated graph; responsive to the transmissionencoding the negative response: re-generating, by the server computer,the graph, wherein the second product sharing the greatest number offeatures with the user, but not with the first product, is closest inproximity, within the generated graph, to the user; rendering, by theserver computer, the user interface comprising the second product. 16.The method of claim 15, further comprising the step of identifying, byhe server computer, the second product as having an idea score greaterthan or equal to a relevancy score calculated according to an averagescore of a plurality of products receiving a positive response from theuser.
 17. The method of claim 15, wherein the plurality of user profiledata and the plurality of product profile data comprise a theme, idea,concept, area of interest comprising: at least one numeric value; or aplurality of keywords or text strings.
 18. The method of claim 15wherein the at least one feature in the plurality of user profile data,and the at least one feature in the plurality of product profile datacomprise: at least one keyword defining a title or a description of theat least one feature; a geography associated with the at least onefeature; an industry category associated with the at least one feature;or at least one additional user associated with the at least one featureand having input the positive response to the first product or thesecond product.
 19. The method of claim 18, wherein the at least onefeature in the plurality of product profile data determines acalculation of an idea score defining a strength of common featuresbetween the user, the first product or the second product.
 20. Themethod of claim 19, wherein the at least one feature associated with theat least one additional user comprises at least one demographic featuregiven a preferential weight in the calculation of the idea score.